Case-Based Reasoning for the Analysis of Methylation Data in Oncology

Researchers seek to identify biological markers which accurately differentiate cancer subtypes and their severity from normal controls. One such biomarker, DNA methylation, has recently become more prevalent in genetic research studies in oncology. This paper proposes to apply these findings in a study of the diagnostic accuracy of DNA methylation signatures for classifying metastasis samples. Very high classification performance measures were obtained from differentially methylated positions and regions, as well as from selected gene signatures. Perfect accuracy was achieved with the top 5 feature-selected genes using three similar cases and the K-nearest neighbor classfier. This work contributes to the path toward the identification of biological signatures for oncology samples using case-based reasoning.